Back to Search
Start Over
Parallel magnetic resonance imaging acceleration with a hybrid sensing approach
- Source :
- Mathematical Biosciences and Engineering, Vol 18, Iss 3, Pp 2288-2302 (2021)
- Publication Year :
- 2021
- Publisher :
- AIMS Press, 2021.
-
Abstract
- In magnetic resonance imaging (MRI), the scan time for acquiring an image is relatively long, resulting in patient uncomfortable and error artifacts. Fortunately, the compressed sensing (CS) and parallel magnetic resonance imaging (pMRI) can reduce the scan time of the MRI without significantly compromising the quality of the images. It has been found that the combination of pMRI and CS can better improve the image reconstruction, which will accelerate the speed of MRI acquisition because the number of measurements is much smaller than that by pMRI. In this paper, we propose combining a combined CS method and pMRI for better accelerating the MRI acquisition. In the combined CS method, the under-sampled data of the K-space is performed by taking both regular sampling and traditional random under-sampling approaches. MRI image reconstruction is then performed by using nonlinear conjugate gradient optimization. The performance of the proposed method is simulated and evaluated using the reconstruction error measure, the universal image quality Q-index, and the peak signal-to-noise ratio (PSNR). The numerical simulations confirmed that, the average error, the Q index, and the PSNR ratio of the appointed scheme are remarkably improved up to 59, 63, and 39% respectively as compared to the traditional scheme. For the first time, instead of using highly computational approaches, a simple and efficient combination of CS and pMRI is proposed for the better MRI reconstruction. These findings are very meaningful for reducing the imaging time of MRI systems.
- Subjects :
- Computer science
Image quality
Acceleration
02 engineering and technology
Iterative reconstruction
Signal-To-Noise Ratio
parallel magnetic resonance imaging (pmri)
Sampling (signal processing)
0502 economics and business
Image Processing, Computer-Assisted
0202 electrical engineering, electronic engineering, information engineering
medicine
QA1-939
Humans
Computer vision
medicine.diagnostic_test
business.industry
k-space
Applied Mathematics
05 social sciences
Magnetic resonance imaging
General Medicine
Magnetic Resonance Imaging
random under-sampling
Nonlinear conjugate gradient method
compressed sensing (cs)
Computational Mathematics
magnetic resonance imaging (mri)
Compressed sensing
Modeling and Simulation
020201 artificial intelligence & image processing
Artificial intelligence
General Agricultural and Biological Sciences
business
Algorithms
050203 business & management
TP248.13-248.65
Mathematics
Biotechnology
Subjects
Details
- Language :
- English
- ISSN :
- 15510018
- Volume :
- 18
- Issue :
- 3
- Database :
- OpenAIRE
- Journal :
- Mathematical Biosciences and Engineering
- Accession number :
- edsair.doi.dedup.....0a73806eeefe9d1498c3bc4c148d6c04